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Apache StreamPipes - A self-service (Industrial) IoT toolbox to enable non-technical users to connect, analyze and explore IoT data streams. This repository contains ready-to-use pipeline elements and adapters for StreamPipes Connect

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Deprecated

The content of this repository was merged into the main repository StreamPipes Extensions

Apache StreamPipes

Apache StreamPipes (incubating) enables flexible modeling of stream processing pipelines by providing a graphical modeling editor on top of existing stream processing frameworks.

It empowers non-technical users to quickly define and execute processing pipelines based on an easily extensible toolbox of data sources, data processors and data sinks. StreamPipes has an exchangeable runtime execution layer and executes pipelines using one of the provided wrappers, e.g., standalone or distributed in Apache Flink.

Pipeline elements in StreamPipes can be installed at runtime - the built-in SDK allows to easily implement new pipeline elements according to your needs. Pipeline elements are standalone microservices that can run anywhere - centrally on your server, in a large-scale cluster or close at the edge.

Extensions: Connect Adapters and Pipeline Elements

This project provides a library of several Connect adapters and pipeline elements that can be used within the Apache StreamPipes toolbox.

See https://streampipes.apache.org/docs/docs/pipeline-elements/ for an overview of currently available pipeline elements.

Contact us if you are missing some pipeline elements!

Installation

The quickest way to run StreamPipes including the latest extensions (adapters, pipeline elements) is by using our Docker-based installation & operation options, namely:

NOTE: StreamPipes CLI & k8s are highly recommended for developers or operators. Standard users should stick to StreamPipes Compose.

Please follow the instructions provided in the corresponding README.md to get started.

For a more in-depth manual, read the installation guide at https://streampipes.apache.org/docs/docs/try-installation.html!

Building StreamPipes Extensions

To properly build the StreamPipes extensions project, the following tools should be installed:

Prerequisites

  • Java 8 JDK (minimum)
  • Maven (tested with 3.6)
  • NodeJS + NPM (tested with v12+/ v6+)
  • Docker + Docker-Compose

Building

To build the extensions project, do the following:

    mvn clean package

Starting

To start StreamPipes Extensions, run docker-compose up -d from the root directory. Make sure the core (incubator-streampipes) is already started.

You can also use the installer or CLI as described in the Getting Started section.

Bugs and Feature Requests

If you've found a bug or have a feature that you'd love to see in StreamPipes, feel free to create an issue in our Jira: https://issues.apache.org/jira/projects/STREAMPIPES

Get help

If you have any problems during the installation or questions around StreamPipes, you'll get help through one of our community channels:

And don't forget to follow us on Twitter!

Contribute

We welcome contributions to StreamPipes. If you are interested in contributing to StreamPipes, let us know! You'll get to know an open-minded and motivated team working together to build the next IIoT analytics toolbox.

Here are some first steps in case you want to contribute:

  • Subscribe to our dev mailing list [email protected]
  • Send an email, tell us about your interests and which parts of Streampipes you'd like to contribute (e.g., core or UI)!
  • Ask for a mentor who helps you understanding the code base and guides you through the first setup steps
  • Find an issue in our Jira which is tagged with a newbie tag
  • Have a look at our developer wiki at https://cwiki.apache.org/confluence/display/STREAMPIPES/Home to learn more about StreamPipes development.

Have fun!

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Apache StreamPipes - A self-service (Industrial) IoT toolbox to enable non-technical users to connect, analyze and explore IoT data streams. This repository contains ready-to-use pipeline elements and adapters for StreamPipes Connect

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